Bipartite Exponential Random Graph Models with Nodal Random Effects

Abstract

We examine the inclusion of specific nodal random effects for first- and second-mode nodes towards an ERGM for bipartite networks. The inclusion of such node-specific random effects in the ERGM accounts for unobserved heterogeneity in the bipartite network and ensures stable estimation results, especially for large-scale bipartite networks. Moreover, The predicted nodal random effects deliver reasonable interpretation to understand the network behavior. The estimation is carried out by an iterative estimation technique, iterating between pseudolikelihood estimation for the nodal random effects and maximum likelihood estimation for the network parameters.